KamalIbrahim01/Ghana-Education-Analytics

# Ghana Education Analytics This project presents an exploratory analysis of anonymized continuous assessment data from a Ghanaian public basic school. The study demonstrates a reproducible education analytics workflow and investigates how student performance varies across subjects and assessment types. ## Study Context The data were collected from a public basic school in Ghana serving upper primary students (Basic Eight). The school follows the national curriculum prescribed by the Ghana Education Service (GES) and serves learners from mixed socioeconomic backgrounds. To protect confidentiality, no identifying information about the school or students is disclosed. A detailed description of the study setting, student population, and assessment structure is provided in `docs/study_context.md`. ## Research Questions 1. How does student performance vary across subjects? 2. How does performance differ by assessment type? 3. Which subjects exhibit high variability, indicating potential learning gaps? 4. How do subjects respond differently to continuous assessment and formal examinations? ## Data - **Raw data**: Microsoft Excel files containing student assessment records (not included for ethical reasons). - **Processed data**: Fully anonymized, long-format dataset used for analysis (`data/processed/assessment_long.csv`). ## Methodology 1. Data auditing and ethical anonymization 2. Reshaping multi-sheet assessment data into tidy long format 3. Exploratory data analysis across subjects and assessment types ## Repository Structure ghana-education-analytics/ ├── notebooks/ # Jupyter notebooks for each project phase ├── data/ │ ├── raw/ # Placeholder only (raw data not shared) │ └── processed/ # Anonymized datasets ├── docs/ # Study context and documentation └── requirements.txt # Python dependencies ## Tools - Python - pandas - matplotlib - Jupyter Notebook ## Ethics All student identifiers were removed prior to analysis. The project uses only anonymized data and i …